Fan Blade Crack Detection Algorithm Based on Multi-Scale Feature Fusion by Yongjun Qi, Hailin Tang, Altangerel Khuder

“…In order to quickly and accurately detect and maintain the fan blades, based on the intelligent big data from the environment, we propose the convolutional neural network model to solve the problem of low recognition rate due to the lack of feature extraction in the fan blade crack image, and the long short-term memory network (Long Short-Term Memory, LSTM) convolutional neural network model, and the dimensionality reduction of the captured image data, which is beneficial to improve the recognition rate of the picture and reduce the loss rate of the picture through the detection model’s suitable recognition of complex background problems such as target occlusion and overlap. …”
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Crack Detection and Evolution Law for Rock Mass under SHPB Impact Tests by Xie Beijing, Dihao Ai, Yu Yang

“…In order to accurately identify and quantitatively calculate the surface cracks of rock mass under SHPB impact loading, an automatic crack detection algorithm was proposed and evaluated by the experiment. …”
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Wireless Multimedia Sensor Network Based Subway Tunnel Crack Detection Method by Bo Shen, Wen-Yu Zhang, Da-Peng Qi, Xiao-Yang Wu

“…Subway tunnel cracks directly reflect the structural integrity of a tunnel, and as such the detection of subway tunnel cracks is always an important task in tunnel structure monitoring. …”
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Numerical study of eddy current by Finite Element Method for cracks detection in structures by S. Harzallah, M. Chabaat, K. Chabane

“…In this paper, we try to use the finite element method of 2-D axisymmetry to solve problems in eddy current testing problems where the main idea is detecting crack's shape using the NDT-EC. Results are given for a simple eddy current problem using the finite element method as a tool to control cracks and defects in materials and eventually, to study their propagation as well as their shape classification. …”
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A Novel Lightweight U-Shaped Network for Crack Detection at Pixel Level by Zhong Luo, Xinle Li, Yanfeng Zheng

Subjects: “…Crack detection…”
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A crack detection and quantification method using matched filter and photograph reconstruction by Liu Zhen-liang, Zhou An, Ran Xin-ru, Wu Yun-peng, Zhao Wei-gang, Zhang Hao

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Mode Selection Model for Rail Crack Detection Based on Ultrasonic Guided Waves by Bo Xing, Zujun Yu, Xining Xu, Liqiang Zhu, Hongmei Shi

“…The model can effectively select guided wave modes suitable for detecting arbitrary cracks on rails, which provides a theoretical solution for rail crack detection.…”
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Concrete Bridge Crack Detection Using Unmanned Aerial Vehicles and Image Segmentation by Yanli Chen, Hongze Li, Hang Zhu, Tianlong Ren, Zhe Cao

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Flexi-YOLO: A lightweight method for road crack detection in complex environments by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

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Research on Road Crack Detection Based on RGB-LPC-GPR Data Fusion by Z. Wang, D. Qiu, R. Wu, R. Wu, Y. Shi, W. Niu

“…This study presents a multimodal data fusion framework for road damage detection and prediction, integrating RGB images, LiDAR point clouds, and GPR (Ground Penetrating Radar) data to enable high-precision detection of surface cracks, potholes, and underground voids, as well as dynamic trend forecasting. …”
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Differential Alternating Current Field Measurement with Deep Learning for Crack Detection and Evaluation by Chenxu Fan, Zhenhu Jin, Jiamin Chen

“…This paper introduces a novel differential TMR-ACFM probe integrated with deep learning for crack detection and evaluation. The differential design effectively mitigates the lift-off effect and external noise, thereby enhancing detection performance without increasing costs. …”
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A Novel YOLO Algorithm Integrating Attention Mechanisms and Fuzzy Information for Pavement Crack Detection by Qingqing Li, Tianshu Wu, Tingfa Xu, Jianmei Lei, Jiu Liu

Subjects: “…Pavement crack detection…”
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Phase transformation surfaces around a crack tip for a shape memory alloys by Christian Lexcellent

Subjects: “…crack detection…”
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Semantic Segmentation Using Lightweight DeepLabv3+ for Desiccation Crack Detection in Soil by Hui Yean Ling, See Hung Lau, Siaw Yah Chong, Min Lee Lee, Yasuo Tanaka

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Signal Enhancement Technology Based on Ultrasonic Guided Wave Rail Bottom Crack Detection by HE Jiping, ZHOU Yongjiu, QIN Pei, ZHANG Yan, ZHOU Shouzhen, WANG Ping, ZHOU Wentao, LIU Yong

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Enhanced YOLOv8-based pavement crack detection: A high-precision approach. by ZuXuan Zhang, HongLi Zhang, TongJia Zhang

“…Crack detection is the key to realize the mechanical and intelligent crack repair. …”
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Evaluating YOLO Models for Efficient Crack Detection in Concrete Structures Using Transfer Learning by Muhammad Sohaib, Muzamal Arif, Jong-Myon Kim

Subjects: “…crack detection…”
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Efficient detection of highway pavement cracks using computer vision-based MSFNet model by Zhengfa Jiang, Danlan Li, Ting Zhao, Mingxing Gao

“…Most highway pavement cracks are long and thin with rich edge details. To balance the needs of pavement crack detection accuracy and real-time performance, while also accounting for local and global feature recognition, a self-focus lightweight crack segmentation method MSFNet based on multilevel correction is proposed. …”
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Enhanced YOLOv8-based pavement crack detection: A high-precision approach by ZuXuan Zhang, HongLi Zhang, TongJia Zhang

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Crack Detection in Single-Crystalline Silicon Wafer Using Laser Generated Lamb Wave by Min-Kyoo Song, Kyung-Young Jhang

“…We firstly verified the identification of S0 and A0 lamb wave modes and then conducted the crack detection under the thermoelastic regime. The experimental results showed that S0 and A0 modes of lamb wave were clearly generated and detected, and in the case of the crack detection, the estimated crack size by 6 dB drop method was almost equal to the actual crack size. …”
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